Big data for twenty-first-century economic statistics

Big data for twenty-first-century economic statistics / edited by Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro.

"The measurement infrastructure for the production of economic statistics in the United States largely was established in the middle part of the 20th century. As has been noted by a number of commentators, the data landscape has changed in fundamental ways since this infrastructure was develope...

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Bibliographic Details
Other Authors: Abraham, Katharine G. (Editor), Jarmin, Ronald S., 1964- (Editor), Moyer, Brian (Editor), Shapiro, Matthew D. (Matthew David) (Editor)
Format: Book
Language:English
Published: Chicago : University of Chicago Press, 2022.
Series:Studies in income and wealth ; v. 79.
Subjects:
Economics > Statistical methods > Data processing.
Big data.
Table of Contents:
  • Introduction. Big data for twenty-first-century economic statistics: the future is now / Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro
  • Toward comprehensive use of big data in economic statistics. Reengineering key national economic indicators / Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ; Big data in the US consumer price index: experiences and plans / Crystal G. Konny, Brendan K. Williams, and David M. Friedman ; Improving retail trade data products using alternative data sources / Rebecca J. Hutchinson ; From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending / Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ; Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data / Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz
  • Uses of big data for classification. Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings / Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ; Automating response evaluation for franchising questions on the 2017 economic census / Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ; Using public data to generate industrial classification codes / John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts
  • Uses of big data for sectoral measurement. Nowcasting the local economy: using Yelp data to measure economic activity / Edward L. Glaeser, Hyunjin Kim, and Michael Luca ; Unit values for import and export price indexes: a proof of concept / Don A. Fast and Susan E. Fleck ; Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data / John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ; Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata / Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland
  • Methodological challenges and advances. Off to the races: a comparison of machine learning and alternative data for predicting economic indicators / Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ; A machine learning analysis of seasonal and cyclical sales in weekly scanner data / Rishab Guha and Serena Ng ; Estimating the benefits of new products / W. Erwin Diewert and Robert C. Feenstra.

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